Biology subjects

Wood, D. K.

Publications and source records attributed to Wood, D. K..

7 recordsLinked to original sources

bioRxiv2026

Integrated ex vivo screening and transcriptomic profiling to prioritize drug combinations for rare cancers

Discovering effective drug combinations requires testing many dose combinations across a diverse panel of tumor models. This approach is limited in rare cancers by a scarcity of cell lines and representative high-throughput models that would make exhaustive screening feasible and predictive. Patient-derived xenograft (PDX) models are genomically representative but too low-throughput for this purpose. Culturing PDX cells ex vivo in three-dimensional (3D) matrices offers a genomically representative and clinically relevant platform for preclinical drug testing, capturing the microenvironmental cues that shape in vivo drug response while requiring only limited tissue per assay. Toward this end, we designed and validated an experimental-computational framework, "ex vivo assessment of combination therapies" (EXACT), to enable drug combination discovery in rare tumors. Using PDX models of malignant peripheral nerve sheath tumors (MPNST), we built a platform to culture PDX cells ex vivo over multiple days, monitoring drug sensitivity and measuring transcriptomic responses to treatment. Computational analysis of these transcriptomic responses then identifies which compensatory pathway creates a unique vulnerability to a second drug. EXACT thus offers a biologically informed, scalable approach for prioritizing drug combinations in rare tumors, nominating drugs alongside biological rationale. Using this methodology, we identified a MEK inhibitor plus HDAC inhibitor combination with enhanced activity in vitro and in vivo, forming the basis of an active clinical trial. This platform could be adapted for real-time use with primary patient specimens, enabling personalized therapeutic discovery. SignificanceEXACT integrates PDX-derived 3D drug screening with biologically informed computational analysis to identify and explain effective combinations, providing a scalable strategy for therapeutic discovery in rare cancers such as MPNST.

cancer biology↗

bioRxiv2025

Suspension physics govern the multiscale dynamics of blood flow in sickle cell disease

In diseases from diabetes to malaria, blood dynamics are significantly altered, resulting in poor clinical outcomes. However, the multiscale mechanisms that determine blood flow in the microcirculation in health and disease are undefined, largely owing to the difficulty in directly linking cell properties to whole-blood rheology. Here, we overcome these difficulties by developing a microfluidic platform to measure red blood cell properties and flow dynamics in the same blood samples from donors. We focus on sickle cell disease (SCD), a genetic disorder that causes red blood cells to stiffen in deoxygenated conditions, with disease pathology driven by oxygen-dependent blood rheology. Our linked cell and whole-blood measurements establish that increases in effective resistances in heterogeneous suspensions are driven by increases in the proportion of stiff cells, similar macroscopically to the behavior of rigid-particle suspensions. Furthermore, by combining simulations with spatially resolved measurements of cell dynamics, we show how the spatio-temporal organization of stiff and deformable cells determines blood rheology and drives disease pathophysiology. In the presence of deformable cells, the stiffened cells marginate towards channel walls, increasing effective wall friction. In fully deoxygenated conditions in which all cells are stiffened, significant heterogeneity in cell volume fraction along the direction of flow causes localized jamming, drastically increasing effective viscous flow resistance. Our work defines the relevant suspension physics required to understand pathological blood rheology in SCD and other diseases affecting red blood cell properties. More broadly, we reveal the multiscale processes that determine emergent rheology in heterogeneous particle suspensions.

physiology↗

bioRxiv2024

Deciphering Colorectal Cancer-Hepatocyte Interactions: A Multiomic Platform for Interrogation of Metabolic Crosstalk in the Liver-Tumor Microenvironment

Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to adapt to and exploit their microenvironment for sustained growth. The liver is a common site of metastasis, but the interactions between tumor cells and hepatocytes remain poorly understood. In the context of liver metastasis, these interactions play a crucial role in promoting tumor survival and progression. This study leverages multiomics coverage of the microenvironment via liquid chromatography and high-resolution, high-mass accuracy mass spectrometry-based untargeted metabolomics, 13C-stable isotope tracing, and RNA sequencing to uncover the metabolic impact of co-localized primary hepatocytes and a colon adenocarcinoma cell line, SW480, using a 2D co-culture model. Metabolic profiling revealed disrupted Warburg metabolism with an 80% decrease in glucose consumption and 94% decrease in lactate production by hepatocyte-SW480 co-cultures relative to SW480 control cultures. Decreased glucose consumption was coupled with alterations in glutamine and ketone body metabolism, suggesting a possible fuel switch upon co-culturing. Further, integrated multiomic analysis indicates that disruptions in metabolic pathways, including nucleoside biosynthesis, amino acids, and TCA cycle, correlate with altered SW480 transcriptional profiles and highlight the importance of redox homeostasis in tumor adaptation. Finally, these findings were replicated in 3-dimensional microtissue organoids. Taken together, these studies support a bioinformatic approach to study metabolic crosstalk and discovery of potential therapeutic targets in preclinical models of the tumor microenvironment.

bioinformatics↗

bioRxiv2023

CDK4/6 inhibition enhances SHP2 inhibitor efficacy and is dependent upon restoration of RB function in malignant peripheral nerve sheath tumors

Malignant peripheral nerve sheath tumors (MPNST) are highly aggressive soft tissue sarcomas with limited treatment options, and novel effective therapeutic strategies are desperately needed. We observe anti-proliferative efficacy of genetic depletion or pharmacological inhibition using the clinically available SHP2 inhibitor (SHP2i) TNO155. Our studies into the signaling response to SHP2i reveal that resistance to TNO155 is partially mediated by reduced RB function, and we therefore test the addition of a CDK4/6 inhibitor (CDK4/6i) to enhance RB activity and improve TNO155 efficacy. In combination, TNO155 attenuates the adaptive response to CDK4/6i, potentiates its anti-proliferative effects, and converges on enhancement of RB activity, with greater suppression of cell cycle and inhibitor-of-apoptosis proteins, leading to deeper and more durable anti-tumor activity in in vitro and in vivo patient-derived models of MPNST, relative to either single agent. Overall, our study provides timely evidence to support the clinical advancement of this combination strategy in patients with MPNST and other tumors driven by loss of NF1.

cancer biology↗

bioRxiv2022

Ex vivo to in vivo model of malignant peripheral nerve sheath tumors for precision oncology

Malignant peripheral nerve sheath tumors (MPNST) are aggressive soft tissue sarcomas that often develop in patients with neurofibromatosis type 1 (NF1-MPNST), but can occur sporadically. Through a multi-institution collaboration, we have developed 13 NF1-associated MPNST patient-derived xenografts (PDX). Genomic analysis of the PDX-tumor pairs identified somatic mutations in NF1 (61%), SUZ12 (61%), EED (15%), and TP53 (15%), and chromosome 8 (Chr8) gain (77%), consistent with published data. Pre-clinical models that capture this molecular heterogeneity are needed to identify and prioritize effective drug candidates for clinical translation. Here, we describe the successful development of a medium-throughput ex vivo 3D microtissue model with several advantages over 2D cell line growth, which can be utilized to predict drug response in vivo. Herein, we present proof-of-principle of this PDX-to-microtissue system, using four genomically representative MPNST and three drugs. This work highlights the development of a novel ex vivo to in vivo preclinical platform in MPNST that successfully captures the genomic diversity observed in patients and represents a resource to identify future therapeutic strategies.

cancer biology↗

bioRxiv2021

Extracellular vesicles mediate the intercellular exchange of nanoparticles

In order to exert their therapeutic effects, nanoparticles (NPs) often need to travel into the tissues composed of multilayered cells. Accumulative evidence has revealed the crucial role of transcellular transport route (entry into one cell, exocytosis, and re-entry into another) in this process. While NP endocytosis and subcellular transport have been intensively characterized, the exocytosis and re-entry steps are poorly understood, which becomes a barrier to improve NP delivery into complex tissues. Here, we termed the exocytosis and re-entry steps together as intercellular exchange. We developed a collagen-based 3D assay to specifically monitor and quantify the intercellular exchange events of NPs, and distinguish the contributions of several potential mechanisms. Our results showed that NPs can be exocytosed freely or enclosed inside extracellular vesicles (EVs) for re-entry, while direct cell-cell contact is hardly involved. EVs account for a significant fraction of NP intercellular exchange, and its importance in NP transport was demonstrated in vitro and in vivo. Intriguingly, while freely released NPs engage with the same cellular receptors for re-entry, EV-enclosed ones bypass this dependence. These studies provide an easy and precise system to investigate the intercellular exchange stage of NP delivery, and shed the first light in the importance of EVs in NP transport between cells and across complex tissues.

pharmacology and toxicology↗

bioRxiv2018

From preliminary to definitive plans: two classes of neurons in frontal eye field

Prior to selecting an action, we often consider other possibilities. How does the brain represent these preliminary plans prior to action selection? Here, we investigated this question in the oculomotor system during self-guided search of natural scenes. We found two classes of neurons in the frontal eye field (FEF): 1) \"late selection neurons\" that represented the selected action plan not long before the upcoming saccade, and 2) \"early selection neurons\" that became predictive of the upcoming saccade much earlier, often before the previous saccade had even ended. Crucially, these early selection neurons did not only predict the upcoming saccade direction; they also reflected the probabilities of possible upcoming saccades, even when they did not end up being selected. Our results demonstrate that during naturalistic eye movements, separate populations of neurons code for preliminary and definitive plans.

neuroscience↗